Deep learning methods for network biology

Lives on earth are regulated by a complex system of interactions. Modelling these interactions through the network paradigms allows researchers to discover and understand the fundamental molecular mechanisms which drive the biological processes and lead to human diseases. The advancement made in the development of sequencing technologies has produced a growing amount of biological data. The aforementioned preconditions are at the base of a flourishing production of deep learning methods able to cope with the complexity and data abundance of this domain. For these reasons, this chapter provides a comprehensive overview of the recent advancements in the deep learning network-based approaches focusing on biology, medicine and pharmacological crucial research problems. At first, the needed biological and network science backgrounds are presented. Second, a comprehensive overview of the biological networks and resources is provided. Finally, we discuss the most recent methods in the field, organising them into three broad categories: the interactome, the network pharmacology, and the frontier biological problems.